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external supervisor

Martin Maiden, Department of  Zoology

Background

Identifying genetic variants that explain population-level differences in bacterial traits including antimicrobial resistance (AMR) is a focus of intense research. We have previously developed computational tools for this purpose (PMID:27572646). While most studies focus on specific cohorts, there is the potential to exploit thousands of genomes in open-science public databases to identify the genetic basis of AMR in diverse pathogens.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

We will identify species-of-interest to focus on from large public databases, and generate assemblies and sequence alignments by creating pipelines of bioinformatics tools. We will optimize the sensitivity of existing approaches by focusing on reference-free, protein-based alignments and pursuing tests for association between AMR and amino acids, proteins and pathways. Discoveries can help combat AMR by improving diagnosis and informing new interventions.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING 

Group members will join weekly lab meetings and attend conferences. University courses are available in R, python and scientific computing.

PROSPECTIVE STUDENT

This project would suit biologists with prior experience of bioinformatics or physical and mathematical scientists with knowledge of genetics.

Supervisors